Market Overview:
The global non-relational SQL market is expected to grow at a CAGR of XX% during the forecast period from 2018 to 2030. The growth in this market can be attributed to the increasing demand for big data and data analytics solutions, growing trend of cloud-based deployments, and rising need for fast and reliable database management systems. The key players in the global non-relational SQL market are Amazon Web Services (AWS), Google, IBM Corporation, Microsoft Corporation, MongoDB Inc., Oracle Corporation, Rackspace Hosting Inc., Salesforce.com Inc., SAP SE and Teradata Corporation.
Product Definition:
Non-relational SQL is a programming language that allows developers to create and manage data without the need for a traditional relational database management system (RDBMS). Non-relational SQL can be used to store and query data in many different formats, including text files, JSON documents, and NoSQL databases.
The importance of Non-relational SQL lies in its ability to work with data in a variety of formats. This flexibility makes it an ideal tool for managing large datasets that are not easily stored or queried using a traditional RDBMS.
Key-Value Store:
Key-value store is a data structure that allows the storage of values with associated keys. The key-value store can be used in various applications such as web services, Enterprise Application Integration (EAI), and document management. Key-value stores are also known as associative memory or indexable storage because the stored information can be organized into key-value pairs.
The major advantage of using KVS is that it reduces database administration costs by eliminating the need for managing tables.
Document Databases:
The document databases and it's usage in non-relational SQL market is expected to grow at a CAGR of XX% over the forecast period. The key drivers for this market are increasing demand for big data solutions, growing cloud computing adoption, rising need to manage digital assets effectively and surge in social media data.
Application Insights:
The data storage application segment dominated the global non-relational SQL market in 2017. Non-relational SQL solutions are widely used for data storage applications as they offer various benefits such as ease of administration, high availability, scalability and manageability over their relational counterparts. The growing demand for storing huge volumes of digital data has led to an increased focus on efficient database management systems that can handle large amounts of information with ease while offering a high level of performance.
Non-relational solutions also provide enhanced capabilities for managing and maintaining a database including the capability to backup & restore the entire content from one instance to another without any loss or corruption in the data itself thereby providing greater assurance regarding ongoing operations. These types of advanced features offered by non- relational SQL databases have resulted in an increased adoption across several industries including ecommerce, social networking, media & entertainment etc., which is expected to drive growth over the forecast period.
Regional Analysis:
North America dominated the global market in 2017, owing to the presence of prominent vendors such as Amazon.com, Inc.; Google; IBM Corporation; Microsoft Corporation; and Oracle Corporation. The region is expected to maintain its dominance over the forecast period due to increasing investments in R&D activities and high adoption rate of non-relational technologies among enterprises for data storage solutions. Moreover, growing demand for cloud computing services is also contributing toward regional growth.
Asia Pacific is anticipated to witness significant growth over the forecast period owing to increasing awareness about emerging technologies along with rising adoption by small & medium organizations (SMOs). Furthermore, government initiatives encouraging SMOs for adopting new technology are further driving regional growth. For instance, according to a white paper published by Infosys Technologies Ltd.
Growth Factors:
- Increased demand for big data analytics and reporting, which is best served by non-relational SQL databases.
- The continued growth of mobile devices and the Internet of Things (IoT), which are generating massive amounts of new data that need to be stored and accessed quickly.
- The increasing popularity of NoSQL databases among developers, who appreciate their flexibility and scalability.
- The growing use of cloud computing, which makes it easy to deploy non-relational SQL databases on demand.
- The emergence of new applications that can take advantage of the unique features offered by non-relational SQL databases
Scope Of The Report
Report Attributes
Report Details
Report Title
Non-relational SQL Market Research Report
By Type
Key-Value Store, Document Databases, Column Based Stores, Graph Database
By Application
Data Storage, Metadata Store, Cache Memory, Distributed Data Depository, e-Commerce, Mobile Apps, Web Applications, Data Analytics, Social Networking
By Companies
Microsoft SQL Server, MySQL, MongoDB, PostgreSQL, Oracle Database, MongoLab, MarkLogic, Couchbase, CloudDB, DynamoDB, Basho Technologies, Aerospike, IBM, Neo, Hypertable, Cisco, Objectivity
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
206
Number of Tables & Figures
145
Customization Available
Yes, the report can be customized as per your need.
Global Non-relational SQL Market Report Segments:
The global Non-relational SQL market is segmented on the basis of:
Types
Key-Value Store, Document Databases, Column Based Stores, Graph Database
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Data Storage, Metadata Store, Cache Memory, Distributed Data Depository, e-Commerce, Mobile Apps, Web Applications, Data Analytics, Social Networking
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Microsoft SQL Server
- MySQL
- MongoDB
- PostgreSQL
- Oracle Database
- MongoLab
- MarkLogic
- Couchbase
- CloudDB
- DynamoDB
- Basho Technologies
- Aerospike
- IBM
- Neo
- Hypertable
- Cisco
- Objectivity
Highlights of The Non-relational SQL Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Key-Value Store
- Document Databases
- Column Based Stores
- Graph Database
- By Application:
- Data Storage
- Metadata Store
- Cache Memory
- Distributed Data Depository
- e-Commerce
- Mobile Apps
- Web Applications
- Data Analytics
- Social Networking
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Non-relational SQL Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
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8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Non-relational SQL is a data storage model that does not use tables. Instead, it uses collections of objects called databases.
Some of the major players in the non-relational sql market are Microsoft SQL Server, MySQL, MongoDB, PostgreSQL, Oracle Database, MongoLab, MarkLogic, Couchbase, CloudDB, DynamoDB, Basho Technologies, Aerospike, IBM, Neo, Hypertable, Cisco, Objectivity.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Non-relational SQL Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Non-relational SQL Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Non-relational SQL Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Non-relational SQL Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Non-relational SQL Market Size & Forecast, 2018-2028
4.5.1 Non-relational SQL Market Size and Y-o-Y Growth
4.5.2 Non-relational SQL Market Absolute $ Opportunity
Chapter 5 Global Non-relational SQL Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Non-relational SQL Market Size Forecast by Type
5.2.1 Key-Value Store
5.2.2 Document Databases
5.2.3 Column Based Stores
5.2.4 Graph Database
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Non-relational SQL Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Non-relational SQL Market Size Forecast by Applications
6.2.1 Data Storage
6.2.2 Metadata Store
6.2.3 Cache Memory
6.2.4 Distributed Data Depository
6.2.5 e-Commerce
6.2.6 Mobile Apps
6.2.7 Web Applications
6.2.8 Data Analytics
6.2.9 Social Networking
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Non-relational SQL Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Non-relational SQL Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Non-relational SQL Analysis and Forecast
9.1 Introduction
9.2 North America Non-relational SQL Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Non-relational SQL Market Size Forecast by Type
9.6.1 Key-Value Store
9.6.2 Document Databases
9.6.3 Column Based Stores
9.6.4 Graph Database
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Non-relational SQL Market Size Forecast by Applications
9.10.1 Data Storage
9.10.2 Metadata Store
9.10.3 Cache Memory
9.10.4 Distributed Data Depository
9.10.5 e-Commerce
9.10.6 Mobile Apps
9.10.7 Web Applications
9.10.8 Data Analytics
9.10.9 Social Networking
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Non-relational SQL Analysis and Forecast
10.1 Introduction
10.2 Europe Non-relational SQL Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Non-relational SQL Market Size Forecast by Type
10.6.1 Key-Value Store
10.6.2 Document Databases
10.6.3 Column Based Stores
10.6.4 Graph Database
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Non-relational SQL Market Size Forecast by Applications
10.10.1 Data Storage
10.10.2 Metadata Store
10.10.3 Cache Memory
10.10.4 Distributed Data Depository
10.10.5 e-Commerce
10.10.6 Mobile Apps
10.10.7 Web Applications
10.10.8 Data Analytics
10.10.9 Social Networking
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Non-relational SQL Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Non-relational SQL Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Non-relational SQL Market Size Forecast by Type
11.6.1 Key-Value Store
11.6.2 Document Databases
11.6.3 Column Based Stores
11.6.4 Graph Database
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Non-relational SQL Market Size Forecast by Applications
11.10.1 Data Storage
11.10.2 Metadata Store
11.10.3 Cache Memory
11.10.4 Distributed Data Depository
11.10.5 e-Commerce
11.10.6 Mobile Apps
11.10.7 Web Applications
11.10.8 Data Analytics
11.10.9 Social Networking
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Non-relational SQL Analysis and Forecast
12.1 Introduction
12.2 Latin America Non-relational SQL Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Non-relational SQL Market Size Forecast by Type
12.6.1 Key-Value Store
12.6.2 Document Databases
12.6.3 Column Based Stores
12.6.4 Graph Database
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Non-relational SQL Market Size Forecast by Applications
12.10.1 Data Storage
12.10.2 Metadata Store
12.10.3 Cache Memory
12.10.4 Distributed Data Depository
12.10.5 e-Commerce
12.10.6 Mobile Apps
12.10.7 Web Applications
12.10.8 Data Analytics
12.10.9 Social Networking
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Non-relational SQL Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Non-relational SQL Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Non-relational SQL Market Size Forecast by Type
13.6.1 Key-Value Store
13.6.2 Document Databases
13.6.3 Column Based Stores
13.6.4 Graph Database
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Non-relational SQL Market Size Forecast by Applications
13.10.1 Data Storage
13.10.2 Metadata Store
13.10.3 Cache Memory
13.10.4 Distributed Data Depository
13.10.5 e-Commerce
13.10.6 Mobile Apps
13.10.7 Web Applications
13.10.8 Data Analytics
13.10.9 Social Networking
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Non-relational SQL Market: Competitive Dashboard
14.2 Global Non-relational SQL Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Microsoft SQL Server
14.3.2 MySQL
14.3.3 MongoDB
14.3.4 PostgreSQL
14.3.5 Oracle Database
14.3.6 MongoLab
14.3.7 MarkLogic
14.3.8 Couchbase
14.3.9 CloudDB
14.3.10 DynamoDB
14.3.11 Basho Technologies
14.3.12 Aerospike
14.3.13 IBM
14.3.14 Neo
14.3.15 Hypertable
14.3.16 Cisco
14.3.17 Objectivity
